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Model Based Design of Chassis-Frame with MATLAB
ISSN: 0148-7191, e-ISSN: 2688-3627
Published November 21, 2019 by SAE International in United States
This content contains downloadable datasetsAnnotation ability available
Event: NuGen Summit
In the current commercial vehicles market, ride-comfort and handling are crucial parameters for the customer and end user. There are various aspects which determine the vehicle behavior. One of aspects is the structural rigidity of the vehicle, which has its own effect on vehicle dynamics. To meet the required stiffness of the main structural component of the vehicle i.e. chassis frame, FEA analysis has to be done in current methodology. The number of iterations have to be done to build an appropriate model with low weight, which can meet the design requirements. At first, conceptual design mock-up unit is to be developed then FEA (CAE) analysis to be done on it. If any design criteria are not met, then this cycle repeats again until it fulfils the required stiffness.
Today, the direct stiffness procedure is the basic principle of almost every FEA software package. In this paper, computer code based on MATLAB software is provided and presented for the analysis of the chassis frame using the direct stiffness method. The code, models a structure of the chassis frame. Model is recognized by collecting and transforming raw data from actual conditions and choosing a mathematical algorithm. With numerous iterations done on MBD, we observed the changes in behavior of frame on how we configure & integrate various members and their corresponding geometry.
Herewith, we are subjecting to lessen the number of repetitions and first-time right design at designer end without much dependency on the FEA software. Engineers detect and address flaws early in structure design. This MBD dramatically improve the design and development efficiency.
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CitationParihar, R., Sharma, G., Patil, N., and Aniya, Y., "Model Based Design of Chassis-Frame with MATLAB," SAE Technical Paper 2019-28-2429, 2019, https://doi.org/10.4271/2019-28-2429.
Data Sets - Support Documents
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